Teams never scale well. When they grow, they introduce a hierarchy. Sub-teams form, requiring management roles to co-ordinate work and facilitate communications. Initially, creating such order brings efficiency gains. But eventually the bureaucracy becomes a burden. Add one layer too many and a tipping point is reached…

In the very over-simplified diagram above, on the left is a single high performing team. Each person has the potential to produce 10 widgets. There is a management overhead cost of 1 widget per person to cover admin, reporting etc. And because the manager is not producing anything, the actual output is 7.9 widgets per person. With other costs taken into account, at least 5 widgets must be produced per person to make a profit. 7.9 makes a pretty good margin. The manager is tasked with growing the team. On the right, we now have the manager with three teams each with a team leader to co-ordinate activities. The extra layer of management is reducing output because more reporting and admin overheads will be created by the hierarchy. The bigger the hierarchy, the further away the decision makers are from the producers and there becomes a disconnect. Those in production roles start to become viewed as a group resource, something that can be easily acquired to scale output. Individuality goes out of the window. The talented ones who don’t move into management roles will leave. The teams become filled with people who have no involvement in decisions lowering commitment and productivity. And so the system declines until output drops below a sustainable level.

So what is the maximum size a hierarchy can grow to before it becomes ineffective?

Back in 2003, I first heard about Robin Dunbar and his magic number 150. The theory being that we are not capable of maintaining more than 150 social connections. And by connections, he meant proper ones. Not online handshakes with ‘friends’. It turned out that he wasn’t the only one to reach this conclusion. The company Gore Associates had already been applying the theory in the design of their offices. Every building had 150 car parking spaces. As soon as people started having to park on the grass, it was time to construct a new plant. I was fascinated by the approach:

Each plant works as a group. There are no bosses. No titles. Salaries are determined collectively. No organization charts, no budgets, no elaborate strategic plans. Wilbert Gore – the late founder of the company, found through trial and error that 150 employees per plant was most ideal. “We found again and again that things get clumsy at a hundred and fifty.”

Source: Robin Dunbar and the magic number 150 by Robert Paterson, January 2003

In recent years, we have seen the rise of online social networks that offer the potential to scale beyond traditional organisational limits. But they bring their own challenges.

Social networks scale but in self-organising and informal ways. Attempts to control a self-organising network will cause it to breakdown – cliques begin to form and a hierarchy inevitably follows. Arguably the effects are worse than attempting to scale teams because networks are susceptible to power laws. When we are faced with many many choices, we tend to be influenced by what other people choose. The more choice, the more likely we will pick from a narrow set of ‘recommendations’, creating a star system. The most popular choices get ever more popular and everything else disappears into the long tail. Whilst a social network can scale, the reality is a tendency to tap into a fraction of its potential value.

The image above (click on the image to view a larger version) is a network graph of programming languages, ranked by number of connections. Assuming you knew nothing about programming languages, which would you be most likely to click on? Most people would go for the most popular choices already. If each click increases the size of the circle, you can see how quickly a star system emerges. The larger the circle, the more likely someone will click on it. The more people click on it, the larger it gets. It’s a closed feedback loop.

Introducing a hierarchy to a social network through rankings or scoring systems that focus on the few, the elite, risks damaging the hidden value – the large volume of untapped knowledge within individuals who will never be regular contributors or part of the star system but who may create unimaginable benefits for just one transaction. Right time, right place, right know-how. Opportunity lies in the unpredictability of networks. Try to create order and that opportunity will be lost.

The true potential offered by social networks is in the ability to dynamically create teams and hierarchies as and when needed from a pot of knowledge that is unlimited in size. And just as quickly dissolve those hierarchies before they take root and begin to skew analysis for future opportunities. Need to discover experts or influencers for a particular project? Mine the network and use predictive analytics to find them based on recent interactions. If they contribute to a team’s success, reward them well for their participation but try and avoid over-promoting their relevance for future projects. Let the network flush out opportunities as and when they arise. Resist the temptation to try and control its power. And accept that sometimes it won’t be the optimal choice – some teams work better than others.

That last point is important as there is another side to this challenge. Success is often attributed to an individual when a (very specific) team effort led to the outcome. Context matters and the world is a lot more chaotic and messy than we like to admit. A football team consisting of the world’s best players would, in theory, be unbeatable. In practice, there’s no certainty.